(DesignNews) Dr. Irfan Siddiqi, a professor of physics at the Quantum Nanoscience Laboratory and the Department of Physics at the University of California Berkeley, is proposing that artificial intelligence is a possible solution that will handle the calculations necessary for quantum computers to function. Dr. Irfan Siddiqi is researching the use of recurrent neural networks to perform quantum signal measurements.
Unlike a traditional bit, which can only be either 1 or 0, a quantum bit (qubit) must exist in a superimposed state, where it is occupying more than one state simultaneously. This is the key to the leap in computing power promised by qubits.
“Can we teach a machine quantum mechanics? Can a machine learn the rules of quantum-mechanics? The answer is, absolutely,” Siddiqi said.
Should quantum computers achieve the level of performance it is theorized they can achieve, many predict artificial intelligence will undergo a similar transformation and see an exponential increase in performance and “intelligence.” Researchers at Google, for example, are already experimenting with “quantum neural networks” to model how neural networks may function and perform on quantum processors.

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